On the Nearest Weighted Point Theorem for Ranking Fuzzy Numbers

On the Nearest Weighted Point Theorem for Ranking Fuzzy Numbers

In this study the author discusses the problem of defuzzification by minimizing the weighted distance between two fuzzy quantities. Also, this study obtains the nearest point with respect to a fuzzy number and shows that this point is unique relative to the weighted distance. By utilizing this point, a method is presented for effectively ranking fuzzy numbers and their images to overcome the de...

On The Ranking Fuzzy Numbers Using Weighted Metric

Ranking Fuzzy Numbers Using a-Weighted Valuations

We studied here on some simple examples the interaction between valuation family, parameters and ranking result. The ranking method studied is based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. The valuation method considered was introduced initially by the Yager and Filev. This valuation consists in...

Ranking L-R Fuzzy Numbers with Weighted Averaging Based on Levels

Ranking of fuzzy numbers based on centroid point and spread

Centroid and spread are commonly used approaches in ranking fuzzy numbers. Some experts rank fuzzy numbers using centroid or spread alone while others tend to integrate them together. Although a lot of methods for ranking fuzzy numbers that are related to both approaches have been presented, there are still limitations whereby the ranking obtained is inconsistent with human intuition. This pape...